Browsing by Subject "1ST-TRIMESTER PREDICTION"

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  • IPPIC Collaborative Network; Snell, Kym I. E.; Allotey, John; Smuk, Melanie; Laivuori, Hannele; Heinonen, Seppo; Kajantie, Eero; Villa, Pia M. (2020)
    Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions: The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice.
  • Keikkala, Elina; Koskinen, Sini; Vuorela, Piia; Laivuori, Hannele; Romppanen, Jarkko; Heinonen, Seppo; Stenman, Ulf-Hakan (2016)
    Background: To study whether maternal serum hyperglycosylated human chorionic gonadotropin (hCG-h) improves first trimester prediction of pre-eclampsia when combined with placental growth factor (PlGF), pregnancy-associated plasma protein-A (PAPP-A) and maternal risk factors. Methods: Gestational-age-adjusted concentrations of hCG, hCG-h, PlGF and PAPP-A were analysed in serum samples by time-resolved immunofluorometric assays at 8-13 weeks of gestation. The case-control study included 98 women who developed pre-eclampsia, 25 who developed gestational hypertension, 41 normotensive women with small-for-gestational-age (SGA) infants and 177 controls. Results: Of 98 women with pre-eclampsia, 24 women developed preterm pre-eclampsia (diagnosis <37 weeks of gestation) and 13 of them had early-onset pre-eclampsia (diagnosis <34 weeks of gestation). They had lower concentrations of PlGF, PAPP-A and proportion of hCG-h to hCG (% hCG-h) than controls. In receiver-operating characteristics (ROC) curve analysis, the area under the curve (AUC) for the combination of PlGF, PAPP-A, % hCG-h, nulliparity and mean arterial blood pressure was 0.805 (95% confidence interval, CI, 0.699-0.912) for preterm pre-eclampsia and 0.870 (95% CI 0.750-0.988) for early-onset pre-eclampsia. Without % hCG-h the AUC values were 0.756 (95% CI 0.651-0.861) and 0.810 (95% CI 0.682-0.938) respectively. For prediction of gestational hypertension, the AUC for % hCG-h was 0.708 (95% CI 0.608-0.808), but for other markers the AUC values were not significant. None of the AUC values were significant for the prediction of SGA infants in normotensive women. Conclusions: First trimester maternal serum % hCG-h tended to improve prediction of preterm and early-onset pre-eclampsia when combined with PlGF, PAPP-A and maternal risk factors.